Multi-axis mechanical arm model consistency control method based on neighbor event driving

Abstract

The invention provides a multi-axis mechanical arm model consistency control method based on neighbor event driving, and the method comprises the steps: firstly building a nonlinear multi-mechanical arm system and a dynamic model of a corresponding mechanical arm, which comprises a leader mechanical arm and a plurality of sub-mechanical arms; the sub-mechanical arm obtains state information of a neighbor sub-mechanical arm according to the neighbor relation; when the leader mechanical arm sends out a leader signal, the sub-mechanical arms obtain state information of the leader mechanical arm and state information of the neighbor sub-mechanical arms according to the state information of the sub-mechanical arms and the connection relation between the sub-mechanical arms and the neighbor mechanical arms, and then consistency error signals of the sub-mechanical arms are calculated; and a neighbor event triggering mechanism and a sub-mechanical arm consistency controller are designed, parameters of the sub-mechanical arm consistency controller are adjusted according to the consistency error signal based on the neighbor event triggering mechanism, and a control signal of the sub-mechanical arm is generated. According to the method, the consistency control problem of the multi-agent system can be solved, a neighbor event triggering mechanism is introduced to reduce the communication load, the communication burden of the system is reduced, and the communication efficiency of the system is improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent collaborative control technology, and more specifically, to a multi-axis robot arm model consistency control method based on neighbor event driving. Background Art

[0002] In multi-agent control systems, communication and computation are important issues. Each sub-agent in the system needs to calculate and process a large amount of data and information. If each sub-agent is interconnected and communicated with other agents in the system, there will inevitably be a large amount of information transmission and computational load, which is a huge burden for the control system. Too frequent communication will also increase the energy consumption of the control system and increase the risk of communication errors.

[0003] The event trigger mechanism sets trigger conditions to limit the interaction and information transmission between sub-agents, so that sub-agents can only communicate under special conditions, thereby reducing the communication burden and computing load. This control method has obvious advantages and is gradually being applied in the control of multi-agents, and has gradually attracted the attention and research of various scientific researchers.

[0004] At the same time, in the field of multi-agent collaborative control, the consistency problem is a basic problem in the control of multi-agent systems. Consistency control aims to achieve consistent states and behaviors of the entire control system. Consistency control involves information exchange, state updates, and decision-making among multiple agents. At present, the consistency control system has the problems of high energy consumption and low communication efficiency. Therefore, it is necessary to study appropriate algorithms and mechanisms to maintain the consistency of the system while maximizing communication efficiency. Summary of the invention

[0005] In order to overcome the consistency control problem of multi-agent systems, the present invention provides a multi-axis robot arm model consistency control method based on neighbor event driving, introduces a neighbor event triggering mechanism to reduce communication load and improve system communication efficiency.

[0006] In order to solve the above technical problems, the technical solution of the present invention is as follows:

[0007] The present invention proposes a multi-axis robot model consistency control method based on neighbor event driving, comprising:

[0008] Establishing a dynamic model of a nonlinear multi-manipulator system and corresponding manipulators, wherein the nonlinear manipulator system includes a leader manipulator and a plurality of sub-manipulators;

[0009] Each of the sub-robotic arms obtains status information of a neighboring sub-robotic arm according to a preset neighbor relationship;

[0010] When the leader manipulator sends a pilot signal, each of the sub-manipulators obtains the state information of the leader manipulator and the state information of the neighboring sub-manipulator according to its own state information and the connection relationship with the neighboring manipulator, and then calculates the consistency error signal of the sub-manipulator;

[0011] For each of the sub-manipulators, design a neighbor event triggering mechanism and a sub-manipulator consistency controller;

[0012] Based on a neighbor event triggering mechanism, the parameters of the sub-mechanical arm consistency controller are adjusted according to the consistency error signal, and the sub-mechanical arm consistency controller is used to generate a control signal for the sub-mechanical arm.

[0013] Furthermore, the preset neighbor relationship includes being set according to the physical distance between the sub-manipulators in the nonlinear multi-manipulator system, being set according to the topological structure between the sub-manipulators in the nonlinear multi-manipulator system, or being set according to the control requirements of the sub-manipulators in the nonlinear multi-manipulator system.

[0014] Furthermore, the dynamic model of the nonlinear multi-manipulator system is:

[0015]

[0016]

[0017] Among them, q i , and Represent the position, velocity and acceleration of the i-th robot arm, τ i and Respectively represent the axis angle and axis angular velocity of the i-th robot arm, u i represents the control input representing the torque of the i-th robot arm, D i , B i 、N i 、M i , H i and K m,i These are all parameters set by the multi-axis robotic arm physical system, and N represents the number of robotic arms.

[0018] Furthermore, the consistency error signal of each sub-mechanical arm includes:

[0019] For each sub-manipulator, the state information of the leader manipulator includes the navigator signal and the connection coefficient with each sub-manipulator; the state information of the neighbor sub-manipulator includes the control signal of the own manipulator and the connection coefficient with the sub-manipulator;

[0020]

[0021] Among them, ei represents the consistency error signal of the ith sub-manipulator, b i is the connection coefficient between the ith child robot and the leader robot, b i =1 means that the i-th child robot can communicate with the leader robot, b i = 0 means that the i-th child robot cannot communicate with the leader robot, a i,j represents the connection coefficient between the ith sub-manipulator and its jth sub-manipulator, a i,j =1 means that the ith sub-manipulator can communicate with its jth sub-manipulator, a i,j = 0 means that the ith sub-manipulator cannot communicate with its jth sub-manipulator, y r is the pilot signal sent by the leader robot, j∈N i Represents the neighboring robot of the i-th child robot.

[0022] Furthermore, the designed neighbor event triggering mechanism includes:

[0023]

[0024] in, Indicates u j,k (t) The value of the control signal after the neighbor event trigger mechanism, u j,k (t) represents the control signal of the kth triggering of the jth neighbor robot of the ith child robot, 0<δ<1, λ 1 (t) and λ 2 (t) are all continuous parameters, satisfying λ *k (t) = 0, λ *k+1 (t) = ±1 and |λ * (t)|≤1;

[0025] When the designed trigger threshold is triggered, the control signal of the neighboring sub-manipulator is transmitted to the sub-manipulator.

[0026] Further, the design consistency controller includes:

[0027] The consistency controller of the i-th sub-manipulator is designed as:

[0028]

[0029] in, yes The estimated value of i represents the control parameters of the ith sub-manipulator, v i Represents the parameter vector of the i-th sub-manipulator.

[0030] Further, adjusting the parameters of the sub-mechanical arm consistency controller according to the consistency error signal based on a neighbor event trigger mechanism, and using the sub-mechanical arm consistency controller to adjust the control signal of the sub-mechanical arm includes:

[0031] Determine whether the consistency error signal of the sub-robotic arm exceeds the trigger threshold. If so, adjust the parameters of the sub-robotic arm controller according to the consistency error signal of the sub-robotic arm, and use the sub-robotic arm consistency controller to adjust the control signal of the sub-robotic arm.

[0032] Furthermore, the method includes a system giving an expected signal, and when the error signal between the leader robot arm signal and the expected signal exceeds a preset trigger threshold, the leader robot arm sends a pilot signal.

[0033] The present invention also proposes a multi-axis robot model consistency control system based on neighbor event driving, which is used to implement the multi-axis robot model consistency control method based on neighbor event driving, comprising:

[0034] A model building module, used to establish a dynamic model of a nonlinear multi-manipulator system and corresponding manipulators, wherein the nonlinear manipulator system includes a leader manipulator and a plurality of sub-manipulators;

[0035] A status information acquisition module, configured for each of the sub-mechanical arms to acquire status information of a neighboring sub-mechanical arm according to a preset neighbor relationship;

[0036] A consistency error calculation module, which is used for, when the leader robotic arm sends a pilot signal, each of the sub-robotic arms obtains the state information of the leader robotic arm and the state information of the neighboring sub-robotic arms according to its own state information and the connection relationship with the neighboring robotic arms, and then calculates the consistency error signal of the sub-robotic arm;

[0037] A neighbor trigger mechanism and consistency controller design module, used for designing a neighbor event trigger mechanism and a sub-manipulator consistency controller for each of the sub-manipulators;

[0038] A control signal generating module is used to adjust the parameters of the sub-mechanical arm consistency controller according to the consistency error signal based on a neighbor event triggering mechanism, and use the sub-mechanical arm consistency controller to generate a control signal for the sub-mechanical arm.

[0039] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above-mentioned methods are implemented.

[0040] Compared with the prior art, the technical solution of the present invention has the following beneficial effects:

[0041] The present invention proposes a multi-axis manipulator model consistency control method based on neighbor event driving. The present invention provides a multi-axis manipulator model consistency control method based on neighbor event driving. First, a nonlinear multi-manipulator system and a dynamic model of a corresponding manipulator are established, including a leader manipulator and a plurality of sub-manipulators; the sub-manipulator obtains the state information of the neighbor sub-manipulator according to the neighbor relationship; when the leader manipulator sends a navigator signal, the sub-manipulator obtains the state information of the leader manipulator and the state information of the neighbor sub-manipulator according to its own state information and the connection relationship with the neighbor manipulator, and then calculates the consistency error signal of the sub-manipulator; the neighbor event triggering mechanism and the sub-manipulator consistency controller are designed, and the parameters of the sub-manipulator consistency controller are adjusted according to the consistency error signal based on the neighbor event triggering mechanism to generate the control signal of the sub-manipulator. The present invention can solve the consistency control problem of the multi-agent system, introduce the neighbor event triggering mechanism to reduce the communication load, reduce the system communication burden, and improve the system communication efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a flow chart of the multi-axis robot model consistency control method based on neighbor event driving described in Example 1;

[0043] Figure 2 This is a diagram of the application scenario of the neighbor event triggering mechanism described in Example 2 in rice field transplanting;

[0044] Figure 3 This is a diagram of the position simulation result of the robotic arm described in Example 2;

[0045] Figure 4 This is a diagram of the speed simulation results of the robotic arm described in Example 2;

[0046] Figure 5 This is a diagram of the acceleration simulation results of the robotic arm described in Example 2;

[0047] Figure 6 This is a simulation diagram of the consistency error of the output signal of the robot arm described in Example 2;

[0048] Figure 7 The graph of the number of times the robot arm events are triggered as described in Example 2;

[0049] Figure 8 This is a schematic diagram of the structure of the multi-axis robotic arm model consistency control system based on neighbor event driving described in Example 3. DETAILED DESCRIPTION

[0050] The drawings are for illustrative purposes only and should not be construed as limiting the present patent;

[0051] In order to better illustrate the present embodiment, some parts in the drawings may be omitted, enlarged or reduced, and do not represent the size of the actual product;

[0052] It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0053] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0054] Example 1

[0055] This embodiment provides a multi-axis robot model consistency control method based on neighbor event driving, such as Figure 1 As shown, including:

[0056] Establishing a dynamic model of a nonlinear multi-manipulator system and corresponding manipulators, wherein the nonlinear manipulator system includes a leader manipulator and a plurality of sub-manipulators;

[0057] Each of the sub-robotic arms obtains status information of a neighboring sub-robotic arm according to a preset neighbor relationship;

[0058] When the leader manipulator sends a pilot signal, each of the sub-manipulators obtains the state information of the leader manipulator and the state information of the neighboring sub-manipulator according to its own state information and the connection relationship with the neighboring manipulator, and then calculates the consistency error signal of the sub-manipulator;

[0059] For each of the sub-manipulators, design a neighbor event triggering mechanism and a sub-manipulator consistency controller;

[0060] Based on a neighbor event triggering mechanism, the parameters of the sub-mechanical arm consistency controller are adjusted according to the consistency error signal, and the sub-mechanical arm consistency controller is used to generate a control signal for the sub-mechanical arm.

[0061] In the specific implementation process, first, each of the sub-robotic arms obtains the status information of the neighbor sub-robotic arms according to the preset neighbor relationship. When the leader robotic arm sends out a navigator signal, each of the sub-robotic arms obtains the status information of the leader robotic arm and the status information of the neighbor sub-robotic arm according to its own status information and the connection relationship with the neighbor robotic arm, and then calculates the consistency error signal of the sub-robotic arm. Finally, the neighbor event triggering mechanism and the sub-robotic arm consistency controller are designed, and the parameters of the sub-robotic arm consistency controller are adjusted according to the consistency error signal based on the neighbor event triggering mechanism, and the sub-robotic arm consistency controller is used to generate the control signal of the sub-robotic arm.

[0062] Example 2

[0063] This embodiment provides a multi-axis robot model consistency control method based on neighbor event driving, including:

[0064] Establishing a dynamic model of a nonlinear multi-manipulator system and corresponding manipulators, wherein the nonlinear manipulator system includes a leader manipulator and a plurality of sub-manipulators;

[0065] The dynamic model of the nonlinear multi-manipulator system is a three-order four-agent nonlinear multi-manipulator system, which is as follows:

[0066]

[0067]

[0068] Among them, q i , and Represent the position, velocity and acceleration of the i-th robot arm, τ i and Respectively represent the axis angle and axis angular velocity of the i-th robot arm, u i represents the control input representing the torque of the i-th robot arm, D i , B i 、N i 、M i , H i and K m,i These are parameters set by the multi-axis robot arm physical system.

[0069] Then by defining and The following parameter strict feedback form is obtained:

[0070]

[0071]

[0072]

[0073] y i =x i,1

[0074] Among them, x i,j represents the i-th robot arm, j=1,2,3 represents the order of each robot arm, y i is the output of the i-th robot arm.

[0075] Each of the sub-robotic arms obtains status information of a neighboring sub-robotic arm according to a preset neighbor relationship;

[0076] The preset neighbor relationship includes being set according to the physical distance between the sub-manipulators in the nonlinear multi-manipulator system, being set according to the topological structure between the sub-manipulators in the nonlinear multi-manipulator system, or being set according to the control requirements of the sub-manipulators in the nonlinear multi-manipulator system.

[0077] For each sub-manipulator, the state information of the leader manipulator includes the navigator signal and the connection coefficient with each sub-manipulator; the state information of the neighbor sub-manipulator includes the control signal of the own manipulator and the connection coefficient with the sub-manipulator;

[0078]

[0079] Among them, e i represents the consistency error signal of the ith sub-manipulator, b i is the connection coefficient between the ith child robot and the leader robot, b i =1 means that the i-th child robot can communicate with the leader robot, b i = 0 means that the i-th child robot cannot communicate with the leader robot, a i,j represents the connection coefficient between the ith sub-manipulator and its jth sub-manipulator, a i,j =1 means that the ith sub-manipulator can communicate with its jth sub-manipulator, a i,j = 0 means that the ith sub-manipulator cannot communicate with its jth sub-manipulator, y r is the pilot signal sent by the leader robot, j∈N i Represents the neighboring robot of the i-th child robot.

[0080] Further define the variable z i,1 and z i,l for:

[0081] z i,1 =e i ,i=1,2,3,4

[0082] z i,l =x i,l -α i,l-1 ,l=2,3

[0083] Based on the backstepping design, for a nonlinear system with a relative order of 3, the following three-step process is designed to obtain the final controller:

[0084] Step 1: It is expressed as:

[0085]

[0086] Among them, θ i ∈Rn and θ j ∈R n is the parameter vector, the nonlinear function φ i,j ∈R n is known, and the first step of the virtual controller α i,1 Set to:

[0087]

[0088] in, X i,j =[x i,1 ,…x i,j ] T ∈R j is a variable vector, and c i,1 is a self-defined positive parameter, and and They are θ i and θ j The estimated amount.

[0089] The Lyapunov candidate function in the first step is set to:

[0090]

[0091] Then its derivative is:

[0092]

[0093] where τ i,1 is the adjustment function of the i-th robot in the first step, τ j,1 is the adjustment function of the jth neighbor robot arm of the i-th robot arm, expressed as:

[0094] τ i,1 =ω i,1 z i,1

[0095] τ j,1 =ω j,1 z i,1

[0096] Step 2: It is expressed as:

[0097]

[0098] where α i,1 The derivative of is:

[0099]

[0100] Get the virtual controller α in the second step i,2 for:

[0101]

[0102] Among them, Γ 1 and Γ 2 is a self-defined symmetric positive definite matrix, and the adjustment function τ of the i-th robot in the second step i,2 and the adjustment function τ of the jth neighbor robot of the i-th robot j,2 for:

[0103] τ i,2 =b i τ i,1 +ω i,2 z i,2

[0104] τ j,2 =a i,j τ j,1 +ω j,1 z i,1

[0105] in, and

[0106] Set the Lyapunov candidate function V in the second step i,2 for:

[0107]

[0108] Combined with the previous definition, we have:

[0109]

[0110] Step 3: According to the definition of error signal and system dynamics model, we can get:

[0111]

[0112] in, is the neighbor control signal, the nonlinear function φ i,0 It is known that if the designed threshold is triggered, the neighbor control signal starts to be transmitted.

[0113] The third step of virtual controller α i,3 Designed for:

[0114]

[0115] Among them, the adjustment function τ of the i-th robot arm in the third step is i,3 and the adjustment function τ of the jth neighbor robot of the i-th robot j,3 They are:

[0116] τi,3 =τ i,2 +ω i,3 z i,3

[0117] τ j,3 =τ j,2 +ω j,3 z j,3

[0118] in, as well as

[0119] The final relative threshold neighbor event triggering mechanism is:

[0120]

[0121] Among them, m j >0 is known, Indicates u j,k (t) The value of the control signal after the event trigger mechanism, u j,k (t) represents the control signal of the kth triggering of the jth neighbor robot of the ith child robot, , 0<δ<1, λ 1 (t) and λ 2 (t) are all continuous parameters, satisfying λ *k (t) = 0, λ *k+1 (t) = ±1 and |λ * (t)|≤1. And t k (k∈Z + ) is the controller update time. The adjacent control signal contains the control coefficient term and the unknown conventional constant term.

[0122] The consistency controller of the i-th sub-manipulator is designed as:

[0123]

[0124] in, yes The estimated value of i represents the control parameters of the ith sub-manipulator, v i represents the parameter vector of the ith sub-manipulator. And the update law of the ith sub-manipulator can be obtained as:

[0125]

[0126] Among them, Γ ρ For a self-defined symmetric positive definite matrix, please note It is possible.

[0127] Define v i =[v i,1 ,vi,2 ,v i,3 ,v i,4 ] T for:

[0128]

[0129]

[0130]

[0131]

[0132] It should be noted that if the initial value is i=1,2,3,4, then at this time, When the above conditions are met, and The update law of must follow the following form:

[0133]

[0134]

[0135] For each of the sub-manipulators, design a neighbor event triggering mechanism and a sub-manipulator consistency controller;

[0136] Based on a neighbor event triggering mechanism, the parameters of the sub-mechanical arm consistency controller are adjusted according to the consistency error signal, and the sub-mechanical arm consistency controller is used to generate a control signal for the sub-mechanical arm.

[0137] Determine whether the consistency error signal of the sub-robotic arm exceeds the trigger threshold. If so, adjust the parameters of the sub-robotic arm controller according to the consistency error signal of the sub-robotic arm, and use the sub-robotic arm consistency controller to adjust the control signal of the sub-robotic arm.

[0138] In this embodiment, the method includes a system giving an expected signal, and when the error signal between the leader robot arm signal and the expected signal exceeds a preset trigger threshold, the leader robot arm sends a pilot signal.

[0139] In order to verify the stability of the system, the final Lyapunov function is set as:

[0140]

[0141] in, By taking the derivative, we can get:

[0142]

[0143] Combining the above formulas, we can get:

[0144]

[0145] Among them, ε 1 , ε 2 , ε 3 , ε 4 They are all set as positive constants to avoid the denominator in the expression being 0.

[0146] As shown in the above formula, the parameters of the adjacent event triggering mechanism can be divided into control coefficient terms, bounded class disturbance terms and adjacent control signal terms. This model can be effectively processed by adding multiple polynomial compensators, namely use You can Rewritten as:

[0147]

[0148] Combined with the update law described above, the derivative of the final Lyapunov function V is expressed as;

[0149]

[0150] in Through integration operation, the inequality can be calculated as:

[0151]

[0152] In summary, based on the principle of stability analysis, we know that V is positive definite. It is negative definite, so the system is stable. The proof is complete.

[0153] In order to avoid the occurrence of Zeno behavior, set a lower bound on the execution interval:

[0154] definition is bounded, we can get:

[0155]

[0156] function Contains variable α i,1 , we can get Right now where ζ is a positive constant. t (t h )=0, we can get Where b is a positive constant.

[0157] Then we get the inequality:

[0158]

[0159] Get the lower bound of the execution interval:

[0160]

[0161] By using the execution interval lower bound, it is possible to prevent an event from being triggered infinitely many times within a limited time interval.

[0162] In this embodiment, the efficiency and scalability of the system are improved by limiting the interaction and information transmission between neighboring robotic arms. In this mechanism, the information transmission and cooperation between sub-robotic arms are restricted by the neighbor relationship, so that each sub-robotic arm only needs to exchange control signals with its neighboring robotic arms, rather than interacting with all sub-robotic arms in the entire control system. The present invention can solve the consistency control problem of multi-agent systems, introduce a neighbor event trigger mechanism to reduce the communication load, reduce the system communication burden, and improve the system communication efficiency.

[0163] In the specific implementation process, the neighbor event triggering mechanism described in this embodiment is applied to the actual rice field transplanting system. Figure 2 As shown in the figure, it is an application scenario diagram of the neighbor event trigger mechanism in rice field transplanting. First, the expected action of rice transplanting is converted into an expected signal and transmitted to the farmland leader robot arm. The error signal obtained by the farmland leader robot arm signal and the expected signal is judged with the event relative threshold; if the trigger threshold is exceeded, the farmland leader robot arm executes the corresponding event to transplant rice and sends out a navigator signal, and communicates and interacts with the farmland sub-robot arm through the neighbor event trigger mechanism. The farmland sub-robot arm tracks the navigator signal to transplant rice, realizes consistent following control, and completes efficient operations in rice fields. Figure 3 , 4 As shown in Figures 5 and 5, they are the simulation results of the position, velocity and acceleration of the robot arm, respectively. It can be seen that the sub-robot arm has the performance of quickly tracking the leader robot arm, as shown in Figure 5. Figure 6 As shown in the figure, it is a simulation diagram of the consistency error of the robot output signal. The consistency error of the robot tracking control has reached the controllable range near the zero point, and has good consistency control performance. Figure 7 As shown, this is a graph of the number of robot arm event triggering times, from which it can be seen that the event threshold condition set by the neighbor event triggering mechanism is feasible.

[0164] Example 3

[0165] This embodiment also provides a multi-axis robot model consistency control system based on neighbor event driving, which is used to implement the multi-axis robot model consistency control method based on neighbor event driving described in embodiment 1 or 2, such as Figure 8 As shown, including:

[0166] A model building module, used to establish a dynamic model of a nonlinear multi-manipulator system and corresponding manipulators, wherein the nonlinear manipulator system includes a leader manipulator and a plurality of sub-manipulators;

[0167] A status information acquisition module, configured for each of the sub-mechanical arms to acquire status information of a neighboring sub-mechanical arm according to a preset neighbor relationship;

[0168] A consistency error calculation module, which is used for, when the leader robotic arm sends a pilot signal, each of the sub-robotic arms obtains the state information of the leader robotic arm and the state information of the neighboring sub-robotic arms according to its own state information and the connection relationship with the neighboring robotic arms, and then calculates the consistency error signal of the sub-robotic arm;

[0169] A neighbor trigger mechanism and consistency controller design module, used for designing a neighbor event trigger mechanism and a sub-manipulator consistency controller for each of the sub-manipulators;

[0170] A control signal generating module is used to adjust the parameters of the sub-mechanical arm consistency controller according to the consistency error signal based on a neighbor event triggering mechanism, and use the sub-mechanical arm consistency controller to generate a control signal for the sub-mechanical arm.

[0171] The same or similar reference numerals correspond to the same or similar components;

[0172] The terms used in the drawings to describe positional relationships are only used for illustrative purposes and should not be construed as limiting this patent;

[0173] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the embodiments here. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A multi-axis robot model consistency control method based on neighbor event driving, characterized in that: include: Establishing a dynamic model of a nonlinear multi-manipulator system and corresponding manipulators, wherein the nonlinear manipulator system includes a leader manipulator and a plurality of sub-manipulators; Each of the sub-robotic arms obtains status information of a neighboring sub-robotic arm according to a preset neighbor relationship; When the leader manipulator sends a pilot signal, each of the sub-manipulators obtains the state information of the leader manipulator and the state information of the neighboring sub-manipulator according to its own state information and the connection relationship with the neighboring manipulator, and then calculates the consistency error signal of the sub-manipulator; For each of the sub-manipulators, design a neighbor event triggering mechanism and a sub-manipulator consistency controller; Based on a neighbor event triggering mechanism, the parameters of the sub-mechanical arm consistency controller are adjusted according to the consistency error signal, and the sub-mechanical arm consistency controller is used to generate a control signal for the sub-mechanical arm.

2. The multi-axis robot model consistency control method based on neighbor event driving according to claim 1 is characterized in that: The preset neighbor relationship includes being set according to the physical distance between the sub-manipulators in the nonlinear multi-manipulator system, being set according to the topological structure between the sub-manipulators in the nonlinear multi-manipulator system, or being set according to the control requirements of the sub-manipulators in the nonlinear multi-manipulator system.

3. The multi-axis robot model consistency control method based on neighbor event driving according to claim 2 is characterized in that: The dynamic model of the nonlinear multi-manipulator system is: Among them, q i , and Represent the position, velocity and acceleration of the i-th robot arm, τ i and Respectively represent the axis angle and axis angular velocity of the i-th robot arm, u i represents the control input representing the torque of the i-th robot arm, D i , B i 、N i 、M i , H i and K m,i These are all parameters set by the multi-axis robotic arm physical system, and N represents the number of robotic arms.

4. The multi-axis robot model consistency control method based on neighbor event driving according to claim 3 is characterized in that: The consistency error signal of each sub-mechanical arm includes: For each sub-manipulator, the state information of the leader manipulator includes the navigator signal and the connection coefficient with each sub-manipulator; the state information of the neighbor sub-manipulator includes the control signal of the own manipulator and the connection coefficient with the sub-manipulator; Among them, e i represents the consistency error signal of the ith sub-manipulator, b i is the connection coefficient between the ith child robot and the leader robot, b i =1 means that the i-th child robot can communicate with the leader robot, b i = 0 means that the i-th child robot cannot communicate with the leader robot, a i,j represents the connection coefficient between the ith sub-manipulator and its jth sub-manipulator, a i,j =1 means that the ith sub-manipulator can communicate with its jth sub-manipulator, a i,j = 0 means that the ith sub-manipulator cannot communicate with its jth sub-manipulator, y r is the pilot signal sent by the leader robot, j∈N i Represents the neighboring robot of the i-th child robot.

5. The multi-axis robot model consistency control method based on neighbor event driving according to claim 4 is characterized in that: The designed neighbor event triggering mechanism includes: in, Indicates u j,k (t) The value of the control signal after the event trigger mechanism, u j,k (t) represents the control signal of the kth trigger of the jth neighbor robot of the ith child robot, 0<δ<1, λ1(t) and λ2(t) are both continuous parameters, satisfying λ *k (t) = 0, λ *k+1 (t) = ±1 and |λ * (t)|≤1; When the designed trigger threshold is triggered, the control signal of the neighboring sub-manipulator is transmitted to the sub-manipulator.

6. The multi-axis robot model consistency control method based on neighbor event driving according to claim 4 is characterized in that: The design consistency controller comprises: The consistency controller of the i-th sub-manipulator is designed as: in, yes The estimated value of i represents the control parameters of the ith sub-manipulator, v i Represents the parameter vector of the i-th sub-manipulator.

7. The multi-axis robot model consistency control method based on neighbor event driving according to claim 6 is characterized in that: Adjusting the parameters of the sub-mechanical arm consistency controller according to the consistency error signal based on a neighbor event trigger mechanism, and using the sub-mechanical arm consistency controller to adjust the control signal of the sub-mechanical arm includes: Determine whether the consistency error signal of the sub-robotic arm exceeds the trigger threshold. If so, adjust the parameters of the sub-robotic arm controller according to the consistency error signal of the sub-robotic arm, and use the sub-robotic arm consistency controller to adjust the control signal of the sub-robotic arm.

8. The multi-axis robot model consistency control method based on neighbor event driving according to claim 7 is characterized in that: The method includes a system giving an expected signal, and when the error signal between the leader mechanical arm signal and the expected signal exceeds a preset trigger threshold, the leader mechanical arm sends a pilot signal.

9. A multi-axis robot model consistency control system based on neighbor event driving, used to implement a multi-axis robot model consistency control method based on neighbor event driving according to any one of claims 1 to 8, characterized in that: include: A model building module, used to establish a dynamic model of a nonlinear multi-manipulator system and corresponding manipulators, wherein the nonlinear manipulator system includes a leader manipulator and a plurality of sub-manipulators; A status information acquisition module, configured for each of the sub-mechanical arms to acquire status information of a neighboring sub-mechanical arm according to a preset neighbor relationship; A consistency error calculation module, which is used for, when the leader robotic arm sends a pilot signal, each of the sub-robotic arms obtains the state information of the leader robotic arm and the state information of the neighboring sub-robotic arms according to its own state information and the connection relationship with the neighboring robotic arms, and then calculates the consistency error signal of the sub-robotic arm; A neighbor trigger mechanism and consistency controller design module, used for designing a neighbor event trigger mechanism and a sub-manipulator consistency controller for each of the sub-manipulators; A control signal generating module is used to adjust the parameters of the sub-mechanical arm consistency controller according to the consistency error signal based on a neighbor event triggering mechanism, and use the sub-mechanical arm consistency controller to generate a control signal for the sub-mechanical arm.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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